CS Departments of Top Universities
- MIT EECS
- Carnegie Mellon University - School of Computer Science
- Stanford Computer Science
- UC Berkeley EECS
- University of Illinois Urbana-Champaign CS
- Cornell CS
- University of Washington CSE
- Georgia Tech - College of Computing
- Princeton CS
- UT Austin CS
- Caltech CMS
- University of Michigan CSE
- Columbia CS
- UCLA CS
- Harvard CS
- University of Pennsylvania CIS
- Yale CS
- University of Wisconsin-Madison CS
- UC San Diego CSE
- University of Maryland CS
CS Courses
Algorithms and Data Structures
- CS 61B: Data Structures - UC Berkeley
- CS 170: Efficient Algorithms and Intractable Problems - UC Berkeley
- 6.006: Introduction to Algorithms - MIT
- 6.046J: Design and Analysis of Algorithms - MIT
- CS 161: Design and Analysis of Algorithms - Stanford
- COS 226: Algorithms and Data Structures - Princeton
- 15-451/651: Algorithms - CMU
Database Systems
- CS 186: Introduction to Database Systems - UC Berkeley
- 15-445/645: Database Systems - CMU
- CS 346: Database System Implementation - Stanford
- 6.5830/6.5831: Database Systems - MIT
Operating Systems
- CS 162: Operating Systems and Systems Programming - UC Berkeley
- 6.S081: Operating System Engineering - MIT
- 15-213/15-513: Introduction to Computer Systems - CMU
- CS 140: Operating Systems - Stanford
- CS 537: Introduction to Operating Systems - Wisconsin
Computer Networks
- CS 144: Introduction to Computer Networking - Stanford
- 6.5840: Distributed Systems - MIT
- CS 168: Introduction to the Internet - UC Berkeley
- 15-441/641: Computer Networks - CMU
Software Engineering
- CS 169: Software Engineering - UC Berkeley
- 6.031: Software Construction - MIT
- CS 107: Programming Paradigms - Stanford
- 15-214: Principles of Software Construction - CMU
Computer Architecture
- CS 61C: Great Ideas in Computer Architecture - UC Berkeley
- 6.004: Computation Structures - MIT
- CS 107: Computer Organization and Systems - Stanford
- 18-447: Introduction to Computer Architecture - CMU
Machine Learning and AI
- CS 189: Introduction to Machine Learning - UC Berkeley
- CS 188: Introduction to Artificial Intelligence - UC Berkeley
- 6.036: Introduction to Machine Learning - MIT
- CS 229: Machine Learning - Stanford
- CS 221: Artificial Intelligence - Stanford
- 10-301/601: Introduction to Machine Learning - CMU
- CS 4780: Machine Learning - Cornell
Compilers
- CS 143: Compilers - Stanford
- 6.035: Computer Language Engineering - MIT
- CS 164: Programming Languages and Compilers - UC Berkeley
- 15-411: Compiler Design - CMU
Discrete Mathematics
- CS 70: Discrete Mathematics and Probability Theory - UC Berkeley
- 6.042J: Mathematics for Computer Science - MIT
- CS 103: Mathematical Foundations of Computing - Stanford
- 15-151: Mathematical Foundations for Computer Science - CMU
Theory of Computation
- CS 172: Computability and Complexity - UC Berkeley
- 6.045J: Automata, Computability, and Complexity - MIT
- CS 154: Introduction to the Theory of Computation - Stanford
- 15-251: Great Ideas in Theoretical Computer Science - CMU
Computer Graphics
- CS 184: Computer Graphics and Imaging - UC Berkeley
- 6.837: Computer Graphics - MIT
- CS 148: Introduction to Computer Graphics - Stanford
- 15-462/662: Computer Graphics - CMU
Computer Security
- CS 161: Computer Security - UC Berkeley
- 6.858: Computer Systems Security - MIT
- CS 155: Computer and Network Security - Stanford
- 15-330: Introduction to Computer Security - CMU
Distributed Systems
- CS 268: Graduate Computer Networks - UC Berkeley
- 6.5840: Distributed Systems - MIT
- CS 244: Advanced Topics in Networking - Stanford
- 15-440/640: Distributed Systems - CMU
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